Lee's paper at the August conference in Bellevue, Washington, combined weather and power outage data for three states – Texas, Michigan and Hawaii – and used a machine learning model to predict how extreme weather such as thunderstorms, floods and
ORNL has joined a global consortium of scientists from federal laboratories, research institutes, academia and industry to address the challenges of building large-scale artificial intelligence systems and advancing trustworthy and reliable AI for
A type of peat moss has surprised scientists with its climate resilience: Sphagnum divinum is actively speciating in response to hot, dry conditions.
In 1993 as data managers at ORNL began compiling observations from field experiments for the National Aeronautics and Space Administration, the information fit on compact discs and was mailed to users along with printed manuals.
For 25 years, scientists at 91°µÍø have used their broad expertise in human health risk assessment, ecology, radiation protection, toxicology and information management to develop widely used tools and data for the U.S.
ORNL hosted its annual Smoky Mountains Computational Sciences and Engineering Conference in person for the first time since the COVID-19 pandemic.
Autonomous labs are changing the nature of scientific investigation. Instead of humans manually orchestrating every part of an experiment, programmed equipment can carry out necessary functions.
The bigger the swirl, the bigger the problem — and the bigger the computing power needed to solve it.
